Evidence map›Paper›PMID 40133199›Full record

ArticleSe pu = Chinese journal of chromatography2025

[Two-dimensional chiral metal-organic-framework nanosheets based on Co-BDC-NH

Mei-Fang Yang, Kang-Ni Zheng, Yi-Xing Long, Yi-Jie Li, Xue-Ping Wang, Jun-Hui Zhang, Li-Ming Yuan

Abstract readEnglish Abstract
In one paragraph

Article in Se pu = Chinese journal of chromatography, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. [Comparison of chiral separation performance of (2-hydroxyethyl-Se pu = Chinese journal of chromatography · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mei-Fang YangSchool of Chemistry and Chemical Engineering, Yunnan Normal University, Kunming 650500, China.
Kang-Ni ZhengSchool of Chemistry and Chemical Engineering, Yunnan Normal University, Kunming 650500, China.
Yi-Xing LongSchool of Chemistry and Chemical Engineering, Yunnan Normal University, Kunming 650500, China.
Yi-Jie LiSchool of Chemistry and Chemical Engineering, Yunnan Normal University, Kunming 650500, China.
Xue-Ping WangSchool of Chemistry and Chemical Engineering, Yunnan Normal University, Kunming 650500, China.
Jun-Hui ZhangSchool of Chemistry and Chemical Engineering, Yunnan Normal University, Kunming 650500, China.
Li-Ming YuanSchool of Chemistry and Chemical Engineering, Yunnan Normal University, Kunming 650500, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two-dimensional metal-organic-framework (2D-MOF) materials have emerged as a new class of functional 2D material. Compared to bulk crystals, 2D-MOFs are easily derivatized, highly porous, and have sufficient active sites. While 2D-MOFs are of considerable research interest, they are also efficient candidates for multiple applications in a variety of fields owing to their numerous advantages. The ability to separate and analyze chiral compounds is greatly significant for progressing human society, and chromatographic separation is widely used in this regard owing to its high resolution and sensitivity. Few reports on the use of 2D-MOFs in chromatographic-separation applications currently exist, and those use gas chromatography to analyze and separate enantiomers are even rarer. Unsurprisingly, the development of novel stationary phases has become a popular topic in the chiral-chromatography field. In this study, 2D-MOF nanosheets (Co-BDC-NH

Indexed as

chiral separationchiral stationary phasegas chromatography (GC)two-dimensional chiral metal-organic-framework nanosheets

Identifiers

PMID40133199
PMCPMC11966380

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.